Jul 12, 2018 · In this paper, we focus on three problems in deep learning based medical image segmentation. Firstly, U-net, as a popular model for medical image segmentation, ...
By using network bridging, a stacked U-net can deal with small datasets and be used in medical image segmentation without a pre-train model. B. Feature Fusion ...
A new smart-cropping pipeline for prostate segmentation using deep learning networks · Medicine, Computer Science. ArXiv · 2021.
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In this study, we describe a deep learning approach, a subset of artificial intelligence, for automatic localization and segmentation of prostates from mpMRI.
This paper provides a comprehensive review of current state-of-the-art convolutional neural networks for 3D prostate segmentation.
We evaluated the proposed method through a comparison with state‐of‐art segmentation methods U‐Net and V‐Net and verified their performance using clinical data.
We make a large-scale empirical comparison of 2.5D segmentation methods with 2D and 3D methods on three representative public datasets involving different ...
... in another research, the. author performed the segmentation of PCa using “2D bridged ... bridged[17]. u-net. 2019 International Joint Conference on Neural ...
In this paper, we develop an optimised state-of-the-art 2D U-Net model by studying the effects of the individual deep learning model components in performing ...
It generates three U-Net (Ronneberger et al., 2015) configurations, including a two-dimensional (2D) U-Net, a three-dimensional. (3D) U-Net operating at full ...